Image processing apparatus, image processing method, storage medium, and program

ABSTRACT

There are provided an image processing apparatus and method. In this apparatus and method, high-frequency components are converted by multiple-frequency transformation in accordance with tone conversion used to change the dynamic range, thereby obtaining a high-quality image. For example, an original image undergoes tone conversion on the basis of a tone conversion curve, and the converted image then undergoes discrete wavelet transformation. After that, subbands obtained by discrete wavelet transformation undergo a conversion process in correspondence with the slope of the tone conversion curve.

TECHNICAL FIELD

The present invention relates to an image processing apparatus, imageprocessing method, storage medium, and program and, more particularly,to an image processing apparatus, image processing method, storagemedium, and program for changing the dynamic range of image data.

BACKGROUND ART

For example, an X-ray chest image has a very broad range of pixel valuessince it is made up of an image region of lungs through which X-rays arereadily transmitted, and an image region of a mediastinal part throughwhich X-rays are hardly transmitted. For this reason, it has beenconsidered to be difficult to obtain an X-ray chest image that allows tosimultaneously observe both the lungs and mediastinal part.

As a method of avoiding this problem, a method described in SPIE Vol.626 Medicine XIV/PACS IV (1986) is known. This method is described usingconstants A, B, and C (for example, A=3, B=0.7) by:S _(D) =A[S _(org) −S _(US) ]+B[S _(US) ]+C  (1)where S_(D) is the pixel value of an image after processing, S_(org) isthe pixel value (input pixel value) of an original image (input image),and S_(US) is the pixel value of a low-frequency image of the originalimage.

This method can change weighting coefficients for high-frequencycomponents (first term) and low-frequency components (second term). Forexample, when A=3 and B=0.7, the effect of emphasizing thehigh-frequency components and compressing the overall dynamic range canbe obtained. Five radiologists evaluated that this method is effectivefor diagnosis compared to an image without any processing.

Japanese Patent No. 2509503 describes a method which is described by:S _(D) =S _(org) +F[G(Px, Py)]  (2)where S_(D) is the pixel value after processing, S_(org) is the originalpixel value (input pixel value), Py is the average profile of aplurality of Y-profiles of an original image, and Px is the averageprofile of a plurality of X-profiles.

The characteristics of the function F(x) will be explained below. If“x>Dth”, F(x) becomes “0”. If “0≦x≦Dth”, F(x) monotonously decreases tohave “E” as a segment and “E/Dth” as a slope. F(x) is given by:F(x)=E−(E/Dth)x, when 0≦x≦Dth =0, when x>Dth  (3)Py=(ΣPyi)/n  (4)Px=(ΣPxi)/n  (5)where (i=1 to n), and Pyi and Pxi are profiles. For example, G(Px, Py)is given by:G(Px, Py)=max(Px, Py)  (6)In this method, of the pixel value (density value) range of the originalimage, the pixel value (density value) range in which the pixel valuesof a low-frequency image are equal to or smaller than Dth is compressed.

As a method similar to the method of Japanese Patent No. 2509503, amethod described in “Anan et. al., Japanese Journal of RadiologicalTechnology, Vol. 45, No. 8, August 1989, p. 1030”, and Japanese PatentNo. 2663189 is known. Using the monotone decreasing function f(x), thismethod is described by:S _(D) =S _(org) +f(S _(US))  (7)S _(US) =ΣS _(org) /M ²  (8)where S_(D) is the pixel value after processing, S_(org) is the originalpixel value, and S_(US) is the average pixel value upon calculating amoving average using a mask size M×M pixels in the original image.

In this method, the low-frequency image generation method is differentfrom that in the method given by equation (2). In the method given byequation (2), a low-frequency image is generated based onone-dimensional data, while in this method, a low-frequency image isgenerated based on two-dimensional data. In this method as well, of thepixel value (density value) range of the original image, the pixel value(density value) range in which the pixel values of a low-frequency imageare equal to or smaller than Dth is compressed.

The aforementioned dynamic range compression method can be expressedusing a function f1( ) of converting (compressing) a low-frequency imageby:S _(D) =f1(S _(US))+(S _(org) −S _(US))  (9)Note that the variable of a function may be omitted for the sake ofsimplicity in this specification.

The dynamic range compression method given by equation (9) will beexplained below. FIGS. 1 and 2 are views for explaining the principle ofthat method. The uppermost view in FIG. 1 shows the profile of an edgeportion of an original image, the middle view shows the profile of asmoothed image of that original image, and the lowermost view shows theprofile of a high-frequency image generated by subtracting the smoothedimage from the original image. In FIG. 2, the uppermost view shows theprofile of an image obtained by multiplying by ½ the absolute values ofthe smoothed image in the middle view of FIG. 1, the middle view showsthe same profile as that of the high-frequency image in FIG. 1, and thelowermost view shows the profile of an image obtained by adding thehigh-frequency image in the interrupt view to the image in the uppermostview obtained by converting the values of the smoothed image. A processfor obtaining an image, the dynamic range of which is compressed, likethe image shown in the lowermost view in FIG. 2, is called a dynamicrange compression process.

In recent years, multiple-frequency processes (to be also referred to asmultiple-frequency transformation processes hereinafter) using Laplacianpyramid transformation and wavelet transformation have been developed.In these multiple-frequency processes, a frequency process (a processfor emphasizing or suppressing specific spatial frequency components) ofan image is implemented by converting Laplacian coefficients or waveletcoefficients obtained by decomposing an image into a plurality offrequency components.

DISCLOSURE OF INVENTION

When the frequency process of an image is implemented using theaforementioned multiple-frequency transformation process, it is rationaland preferable to also implement a dynamic range change process usingthe multiple-frequency transformation process.

It is an object of the present invention to obtain a high-quality outputimage by exploiting a tone conversion process and multiple-frequencytransformation process, to implement a dynamic range change processusing the multiple-frequency transformation process, or to obtain ahigh-quality output image, the dynamic range or predetermined pixelvalue range (partial pixel value range) of which has been changed usingthe tone conversion process and multiple-frequency transformationprocess.

According to the first aspect of the present invention, there isprovided an image processing apparatus comprising tone conversion meansfor executing tone conversion of an image, and component conversionmeans for converting frequency components of a plurality of frequencybands of the image or an image after that image has undergone toneconversion by the tone conversion means, on the basis of tone conversioncharacteristics of the tone conversion means.

According to the second aspect of the present invention, there isprovided an image processing apparatus comprising tone conversion meansfor executing tone conversion of an image, frequency transformationmeans for decomposing the image that has undergone tone conversion bythe tone conversion means into frequency components of a plurality offrequency bands, and component conversion means for converting thefrequency components of the plurality of frequency bands obtained by thefrequency transformation means, on the basis of tone conversioncharacteristics of the tone conversion means.

According to the third aspect of the present invention, there isprovided an image processing apparatus comprising first frequencytransformation means for decomposing an image into first frequencycomponents of a plurality of frequency bands, tone conversion means forexecuting tone conversion of the image, second frequency transformationmeans for decomposing the image that has undergone tone conversion bythe tone conversion means into second frequency components of aplurality of frequency bands, and component conversion means forconverting the second frequency components of the plurality of frequencybands by adding frequency components, which are obtained by convertingthe first frequency components of the plurality of frequency bands onthe basis of tone conversion characteristics of the tone conversionmeans, to the second frequency components of the plurality of frequencybands.

According to the fourth aspect of the present invention, there isprovided an image processing apparatus comprising tone conversion meansfor executing tone conversion of an image, frequency transformationmeans for decomposing the image into frequency components of a pluralityof frequency bands, component conversion means for converting thefrequency components of a plurality of frequency bands obtained by thefrequency transformation means, on the basis of tone conversioncharacteristics of the tone conversion means, inverse frequencytransformation means for generating an image by compositing thefrequency components converted by the component conversion means, andaddition means for adding the image generated by the inverse frequencytransformation means and the image that has undergone tone conversion bythe tone conversion means.

According to the fifth aspect of the present invention, there isprovided an image processing apparatus comprising frequencytransformation means for decomposing an image into frequency componentsof a plurality of frequency bands, component conversion means forconverting the frequency components of the plurality of frequency bandsobtained by the frequency transformation means, on the basis ofpredetermined tone conversion characteristics, inverse frequencytransformation means for generating an image by compositing thefrequency components converted by the component conversion means, andtone conversion means for executing tone conversion of the imagegenerated by the inverse frequency transformation means, on the basis ofthe predetermined tone conversion characteristics.

According to the sixth aspect of the present invention, there isprovided an image processing method comprising the tone conversion stepof executing tone conversion of an image, and the component conversionstep of converting frequency components of a plurality of frequencybands of the image or an image after that image has undergone toneconversion in the tone conversion step, on the basis of tone conversioncharacteristics of the tone conversion step.

According to the seventh aspect of the present invention, there isprovided an image processing method comprising the tone conversion stepof executing tone conversion of an image, the frequency transformationstep of decomposing the image that has undergone tone conversion in thetone conversion step into frequency components of a plurality offrequency bands, and the component conversion step of converting thefrequency components of the plurality of frequency bands obtained in thefrequency transformation step, on the basis of tone conversioncharacteristics of the tone conversion step.

According to the eighth aspect of the present invention, there isprovided an image processing method comprising the first frequencytransformation step of decomposing an image into first frequencycomponents of a plurality of frequency bands, the tone conversion stepof executing tone conversion of the image, the second frequencytransformation step of decomposing the image that has undergone toneconversion in the tone conversion step into second frequency componentsof a plurality of frequency bands, and the component conversion step ofconverting the first frequency components of the plurality of secondfrequency bands by adding frequency components, which are obtained byconverting the first frequency components of the plurality of frequencybands on the basis of tone conversion characteristics of the toneconversion step, to the second frequency components of the plurality offrequency bands.

According to the ninth aspect of the present invention, there isprovided an image processing method comprising the tone conversion stepof executing tone conversion of an image, the frequency transformationstep of decomposing the image into frequency components of a pluralityof frequency bands, the component conversion step of convertingfrequency components of the plurality of frequency bands obtained in thefrequency transformation step, on the basis of tone conversioncharacteristics of the tone conversion step, the inverse frequencytransformation step of generating an image by compositing the frequencycomponents converted in the component conversion step, and the additionstep of adding the image generated in the inverse frequencytransformation step and the image that has undergone tone conversion inthe tone conversion step.

According to the 10th aspect of the present invention, there is providedan image processing method comprising the frequency transformation stepof decomposing an image into frequency components of a plurality offrequency bands, the component conversion step of converting thefrequency components of the plurality of frequency bands obtained in thefrequency transformation step, on the basis of predetermined toneconversion characteristics, the inverse frequency transformation step ofgenerating an image by compositing the frequency components converted inthe component conversion step, and the tone conversion step of executingtone conversion of the image generated in the inverse frequencytransformation step, on the basis of the predetermined tone conversioncharacteristics.

The above and other objects, effects, and features of the presentinvention will become apparent from the description of embodiments to bedescribed hereinafter with reference to the accompanying drawings.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a chart for explaining prior art of dynamic range compression;

FIG. 2 is a chart for explaining prior art of dynamic range compression;

FIG. 3 is a block diagram of an image processing apparatus according toEmbodiment 1;

FIG. 4 is a flow chart showing the processing sequence of the imageprocessing apparatus according to Embodiment 1;

FIG. 5 shows an example of a tone conversion curve used to change thedynamic range;

FIGS. 6A to 6C are explanatory views of discrete wavelet transformationand inverse discrete wavelet transformation;

FIG. 7 shows a frequency coefficient conversion curve;

FIG. 8 shows a frequency coefficient conversion curve;

FIG. 9 is a flow chart showing the processing sequence of the imageprocessing apparatus according to Embodiment 2;

FIG. 10 is a flow chart showing the processing sequence of the imageprocessing apparatus according to Embodiment 3;

FIG. 11 is a block diagram of an image processing apparatus according toEmbodiment 4;

FIG. 12 is a flow chart showing the processing sequence of the imageprocessing apparatus according to Embodiment 4; and

FIG. 13 shows a curve used to convert frequency coefficients.

BEST MODE OF CARRYING OUT THE INVENTION Embodiment 1

FIG. 3 shows an X-ray photographing apparatus 100 according toEmbodiment 1. The X-ray photographing apparatus 100 has a function ofexecuting processes for respective frequency bands of a taken image, andcomprises a pre-processing circuit 106, CPU 108, main memory 109,control panel 110, image display 111, and image processing circuit 112,which exchange data via a CPU bus 107.

The X-ray photographing apparatus 100 also comprises a data acquisitioncircuit 105 connected to the pre-processing circuit 106, and atwo-dimensional X-ray sensor 104 and X-ray generation circuit 101, whichare connected to the data acquisition circuit 105, and these circuitsare also connected to the CPU bus 107.

In the aforementioned X-ray photographing apparatus 100, the main memory109 stores various data and the like required for the processing by theCPU 108, and includes a work memory for the CPU 108.

The CPU 108 executes operation control and the like of the overallapparatus in accordance with operations at the control panel 110. As aresult, the X-ray photographing apparatus 100 operates as follows.

The X-ray generation circuit 101 emits an X-ray beam 102 toward anobject 103 to be examined. The X-ray beam 102 emitted by the X-raygeneration circuit 101 is transmitted through the object 103 to beexamined while being attenuated, and reaches the two-dimensional X-raysensor 104. The two-dimensional X-ray sensor 104 detects an X-ray image.Assume that the X-ray image is, for example, a human body image or thelike in this embodiment.

The data acquisition circuit 105 converts X-ray image information(electrical signal) output from the two-dimensional X-ray sensor 104into a predetermined electrical signal, and supplies that signal to thepre-processing circuit 106. The pre-processing circuit 106 executespre-processes such as offset correction, gain correction, and the likefor the signal (X-ray image signal) from the data acquisition circuit105. The X-ray image signal that has undergone the pre-processes by thepre-processing circuit is transferred as an original image to the mainmemory 109 and image processing circuit 112 via the CPU bus 107 underthe control of the CPU 108.

Reference numeral 112 denotes a block diagram showing the arrangement ofthe image processing circuit. In the image processing circuit 112,reference numeral 113 denotes a tone conversion circuit for performingtone conversion of the original image; 114, a discrete wavelettransformation circuit for computing the discrete wavelet transforms (tobe referred to as DWTs hereinafter) of the original image that hasundergone the tone conversion by the tone conversion circuit 113 toobtain image components (wavelet transform coefficients) of respectivefrequency bands; 115, a component conversion circuit for converting theimage components of the respective frequency bands obtained by thediscrete wavelet transformation circuit 114; and 116, an inverse DWTcircuit for computing the inverse discrete wavelet transforms (to bereferred to as inverse DWTs hereinafter) on the basis of the imagecomponents converted by the component conversion circuit 115.

FIG. 4 is a flow chart showing the flow of processes in the imageprocessing circuit 112, FIG. 5 shows an example of a tone conversioncurve used to change the dynamic range of image data by the toneconversion circuit 113, FIG. 6A is a circuit diagram showing thearrangement of the DWT circuit 114, FIG. 6B shows an example of theformat of transform coefficient groups of two levels obtained by atwo-dimensional transformation process, and FIG. 6C is a circuit diagramshowing the arrangement of the inverse DWT circuit 116. FIGS. 7 and 8show examples of function forms used to change image components (DWTcoefficients).

The processing in Embodiment 1 will be explained below along with theflow of processes shown in FIG. 4.

An original image that has undergone the pre-processes in thepre-processing circuit 106 is transferred to the image processingcircuit 112 via the CPU bus 107.

In the image processing circuit 112, the tone conversion circuitconverts an original image Org(x, y) into f(Org(x, y) using a toneconversion curve f( ) (s201). In this specification, a “curve” may beused synonymously with a “function”. Note that x and y are thecoordinates on the original image. As the tone conversion curve f( ),for example, a curve form shown in FIG. 5 is used. For example, solidline 1 is a function with slope=1. That is, input and output values arenot changed (input and output values are equal to each other), and nodynamic range compression effect is expected. Broken line 2 indicates afunction form for compressing the dynamic range on the low pixel valueside, and broken line 3 indicates a function form for expanding thedynamic range on the low pixel value side. Likewise, broken line 4expands the dynamic range on the high pixel value side, and broken line5 indicates a function form for compressing the dynamic range on thehigh pixel value side.

In practice, these curve forms are preferably formed to be differentialcontinuous (differentiable and continuous functions). This is because afalse edge may be generated when the tone conversion curve includes anundifferentiable or discontinuous point.

The DWT circuit (discrete wavelet transformation circuit) 114 executes atwo-dimensional discrete wavelet transformation process of the imagef(Org(x, y) after tone conversion, and calculates and outputs imagecomponents (to be also referred to as transform coefficients orfrequency coefficients hereinafter). The image data stored in the mainmemory 109 is sequentially read out and undergoes the transformationprocess by the DWT circuit 114, and is written in the main memory 109again. In the DWT circuit 114 of this embodiment, an input image signalis separated into odd and even address signals by a combination of adelay element and down samplers, and undergoes filter processes of twofilters p and u. In FIG. 6A, s and d represent low- and high-passcoefficients upon decomposing a linear image signal to one level, andare respectively computed by:d(n)=x(2*n+1)−floor((x(2*n)+x(2*n+2))/2)  (11)s(n)=x(2*n)+floor((d(n −l)+d(n))/4)  (12)

where x(n) is an image signal to be transformed.

With the above process, a linear discrete wavelet transformation processis done for an image signal. Since two-dimensional discrete wavelettransformation is implemented by sequentially executing linear discretewavelet transformation in the horizontal and vertical directions of animage and its details are known to those who are skilled in the art, adescription thereof will be omitted. FIG. 6B shows an example of theformat of transform coefficient groups of two levels obtained by thetwo-dimensional discrete wavelet transformation process. An image signalis decomposed into image components HH1, HL1, LH1, . . . , LL indifferent frequency bands (s202). In FIG. 6B, each of HH1, HL1, LH1, . .. , LL (to be referred to as subbands hereinafter) indicates an imagecomponent for each frequency band.

The component conversion circuit converts image component hn(x, y) ofeach subband (S203) by:h2n(x, y)=(1/f′(Org(x, y)))×hn(x, y)  (13)where h2n(x, y) is the converted image component, and n is the subbandcategory.

With this process, image components after the tone conversion process,which become f′ ( ) times (f′ ( ) is the slope of the tone conversioncurve f( ) in Org(x, y) corresponding to hn(x, y)) of those of theoriginal image Org(x, y) by the tone conversion process, can beconverted into values nearly equal to those of the original image Org(x,y). Note that the image components of the LL subband as thelow-frequency component of the lowermost layer are not changed. Hence,the dynamic range of the overall image is changed, but image componentscorresponding to high-frequency components can maintain values nearlyequal to those of the original image. Note that the right-hand side ofequation (13) may be multiplied by a predetermined constant. In thiscase, the high-frequency components of an image can be adjusted(emphasized or suppressed) while changing the dynamic range.

Also, the right-hand side of equation (13) may be multiplied by apredetermined function having a curve form which depends on the pixelvalues of the original image Org(x, y) or its smoothed image. Suchfunction has a curve form that assumes a small value when the pixelvalue of the original image Org(x, y) or its smoothed image is equal toor lower than a predetermined pixel value, or assumes a large value whenthe pixel value is higher than the predetermined pixel value. In suchcase, for example, the absolute values of high-frequency components in alow pixel value region can be suppressed, and noise components can bemade less conspicuous.

The image, the dynamic range of which has been changed by the toneconversion process, does not suffer any artifacts such as overshoot andthe like. However, the process given by equation (13) can amplifyhigh-frequency components by changing them, but artifacts such asovershoot and the like may be generated.

To prevent generation of such artifacts, in place of equation (13), itis effective to change high-frequency components by:h2n(x, y)=hn(x, y)+(1/f′(Org(x, y))−1) ×fn(hn(x, y))  (14)

Note that the function fn( ) has a curve form shown in FIG. 7 or 8. InFIGS. 7 and 8, the abscissa plots the input coefficients, and theordinate plots the output coefficients. FIGS. 7 and 8 show conversioncurves when the frequency coefficients are +, and the same conversion ismade even when the frequency coefficients are −. That is, FIGS. 7 and 8show only the first quadrant of an odd function. In this specification,all functions used to convert frequency coefficients (high-frequencycomponents or high-frequency coefficients) are odd functions, and onlytheir first quadrants are shown. These curves are differentialcontinuous (differentiable and continuous functions), and can preventgeneration of any false edges. Image components generated at an edgehave values larger than normal components, and these curve forms setimage components corresponding to edge components to be 0 or suppressthem. As a result, in equation (14), when an image component is large,fn(hn(x, y)) becomes 0 or a suppressed value, and h2n(x, y) becomesnearly equal to hn(x, y) or a suppressed value (a value smaller than animage component of the original image). On the other hand, when an imagecomponent has a normal value, h2n(x, y) given by equation (14) becomesthe same value as equation (13).

In this way, the dynamic range is changed, and effective imagecomponents (those equal to or lower than the predetermined value) of thehigh-frequency components become equal to those of the image before toneconversion. Since image components (those higher than the predeterminedvalue) that cause overshoot of the high-frequency components are notadded, i.e., changed, or are added or changed while being suppressed,overshoot or the like can be prevented or suppressed. By setting theslope of the function form fn( ) to be equal to or larger than 1 (orlarger than 1) within the range where the input value is equal to orsmaller than the predetermined value, high-frequency components can beemphasized while suppressing overshoot. Hence, the dynamic range andhigh-frequency components can be simultaneously changed whilesuppressing overshoot and the like.

The inverse DWT circuit 116 computes the inverse discrete wavelettransforms of image components (transform coefficients) converted by thecomponent conversion circuit 115 as follows (s204). The converted imagecomponents stored in the main memory 109 are sequentially read out andundergo the inverse transformation process by the inverse discretewavelet transformation circuit 116, and are written in the main memory109 again. Assume that the arrangement of the inverse discrete wavelettransformation of the inverse DWT circuit 116 in this embodiment is asshown in FIG. 6C. Input image components undergo filter processes usingtwo filters u and p, and are added to each other after being up-sampled,thus outputting an image signal x′. These processes are described by:x′(2*n)=s′(n)−floor((d′(n−1)+d′(n))/4)  (15)x′(2*n+1)=d′(n)+floor((x′(2*n)+x′(2*n+2 )) /2)  (16)

With the above process, linear inverse discrete wavelet transformationof transform coefficients is done. Since two-dimensional inversediscrete wavelet transformation is implemented by sequentially executinglinear inverse transformation in the horizontal and vertical directionsof an image and its details are known to those who are skilled in theart, a description thereof will be omitted.

As described above, since the dynamic range change process isimplemented by exploiting the multiple-frequency transformation process,and high-frequency components are adjusted in correspondence with toneconversion used to change the dynamic range, a high-quality outputimage, the dynamic range of which has been changed, can be obtained.Also, the dynamic range of an image can be changed, and high-frequencycomponents can be changed at the same time, while suppressing artifactssuch as overshoot and the like. In this manner, a dynamic range changeprocess such as dynamic range compression or the like and a sharpeningprocess for each frequency band by changing frequency components foreach frequency band can be simultaneously executed.

Embodiment 2

Embodiment 2 will be described below along with the flow of processesshown in FIG. 9. A description of the same processes as those inEmbodiment 1 will be omitted.

The DWT circuit 114 executes a DWT process of an original image Org(x,y). Let horgn(x, y) be each image component obtained by that process(s601) The tone conversion circuit 113 executes a tone conversionprocess of the original image Org(x, y) using a tone conversion curve f() (s602). The DWT circuit 114 executes a DWT process of the imagef(Org(x, y)) that has undergone the tone conversion process to obtainimage components hn(x, y) (s603). Note that n indicates the subbandcategory and x and y are the coordinates as in Embodiment 1.

The component conversion circuit 115 adds image component horgn(x, y) tothe image component hn(x, y) to obtain a new image component h2n(x, y)(s604) by:h2n(x, y)=hn(x, y)+(1−f′(Org(x, y))) ×horgn(x, y)  (17)

Note that the image components of the LL subband as the low-frequencycomponent of the lowermost layer are not changed. In this manner, themagnitudes of high-frequency components of the image, the dynamic rangeof which has been changed can be maintained to be nearly equal to thoseof high-frequency components of the original image. In this case, sincethe high-frequency components are added using those of the originalimage, the magnitudes of the high-frequency components can accuratelycome closer to those of the high-frequency components of the originalimage. Note that the second term of the right-hand side of equation (17)may be multiplied by a predetermined constant. In this case, thehigh-frequency components of the image can be adjusted (emphasized orsuppressed) while changing the dynamic range.

Note that equation (18) may be used in place of equation (17) to obtainthe same effect:i h2n(x, y)=horgn(x, y)  (18)

Also, the right-hand side of equation (17) may be multiplied by apredetermined function having a curve form which depends on the pixelvalues of the original image Org(x, y) or its smoothed image. Suchfunction has a curve form that assumes a small value when the pixelvalue of the original image Org(x, y) or its smoothed image is equal toor lower than a predetermined pixel value, or assumes a large value whenthe pixel value is higher than the predetermined pixel value.

The image, the entire dynamic range of which has been changed by thetone conversion process, does not suffer any artifacts such as overshootand the like. However, the process given by equation (17) can amplifyhigh-frequency components by adding those of the original image, butsimultaneously adds components of the original image which may causeartifacts such as overshoot and the like. Hence, overshoot may occur.

To prevent this, in place of equation (17), it is effective to changehigh-frequency components by:h2n(x, y)=hn(x, y)+(1−f′(Org(x, y))) ×fn(horgn(x, y))  (19)

Note that the function fn( ) has a curve form shown in FIG. 7 or 8.Image components generated at an edge have values larger than normalcomponents, and these curve forms set image components corresponding toedge components to 0 or suppress them. As a result, in equation (19),when an image component is large, fn(horgn(x, y)) becomes 0 or asuppressed value, and h2n(x, y) becomes nearly equal to hn(x, y) or asuppressed value smaller than horgn(x, y). On the other hand, when animage component has a normal value, h2n(x, y) becomes the same value asequation (17).

In this way, the dynamic range is changed, and effective imagecomponents (those equal to or lower than the predetermined value) of thehigh-frequency components become nearly equal to those of the imagebefore tone conversion. Since image components (those higher than thepredetermined value) that cause overshoot of the high-frequencycomponents are not added, i.e., changed, or are added or changed whilebeing suppressed, overshoot or the like can be prevented or suppressed.By setting the slope of the function form fn( ) to be equal to or largerthan 1 (or larger than 1) within the range where the input value isequal to or smaller than the predetermined value, high-frequencycomponents can be emphasized while suppressing overshoot. Hence, thedynamic range and high-frequency components can be changed at the sametime while suppressing overshoot and the like.

The inverse DWT circuit 116 executes an inverse DWT process based on theimage components changed by the component change circuit 115 (S605).

In Embodiment 2, since the dynamic range change process is implementedby exploiting the multiple-frequency process, and high-frequencycomponents are adjusted in correspondence with tone conversion used tochange the dynamic range, a high-quality image, the dynamic range ofwhich has been changed, can be obtained. Furthermore, sincehigh-frequency components of the original image are used as those to beadded, high-frequency components of the processed image can accuratelycome closer to those of the original image. Also, the dynamic range andhigh-frequency components can be changed at the same time whilesuppressing artifacts such as overshoot and the like. In this manner, adynamic range change process such as dynamic range compression or thelike and a sharpening process for each frequency band by changingfrequency components for each frequency band can be simultaneouslyexecuted to obtain a high-quality output image.

Embodiment 3

Embodiment 3 will be described along with the flow of processes shown inFIG. 10. A description of the same processes as those in Embodiment 1will be omitted.

The tone conversion circuit 113 executes a tone conversion process of anoriginal image Org(x, y) using a tone conversion curve f( ) to obtain aprocessed image f(Org(x, y) (s701). The DWT circuit 114 then executes aDWT process of the original image to obtain image components hn(x, y)(s702). Note that n indicates the subband category and x and y are thecoordinates as in Embodiment 1.

The component conversion circuit 115 converts each image component hn(x,y) by:h2n(x, y)=(1−f′(Org(x, y)))×hn(x, y)  (20)to obtain a new image component h2n(x, y) (s703).

Furthermore, the values of the lowest frequency component LL are set tobe all 0s (zeros).

In this way, upon restoring an image from h2n(x, y), an image Hr(x, y)consisting of only high-frequency components depending on the slope ofthe tone conversion curve can be obtained. Note that the right-hand sideof equation (20) may be multiplied by a predetermined constant. In thiscase, the high-frequency components of the image can be adjusted(emphasized or suppressed) while changing the dynamic range.

Also, the right-hand side of equation (20) may be multiplied by apredetermined function having a curve form which depends on the pixelvalues of the original image Org(x, y) or its smoothed image. Suchfunction has a curve form that assumes a small value when the pixelvalue of the original image Org(x, y) or its smoothed image is equal toor lower than a predetermined pixel value, or assumes a large value whenthe pixel value is higher than the predetermined pixel value.

The inverse DWT circuit 116 computes the inverse DWTs based on thecomponents converted by the component conversion circuit 115 to obtain arestored image Hr(x, y) (s704) . The image f(Org(x, y) obtained by thetone conversion circuit 113 is added to the image Hr(x, y) obtained bythe inverse DWT circuit 116 by:Prc(x, y)=f(Org(x, y))+Hr(x, y)  (21)to obtain a processed image Prc(x, y) (s705).

The image, the dynamic range of which has been changed by the toneconversion process, does not suffer any artifacts such as overshoot andthe like. However, the high-frequency components obtained by equation(20) contain components of the original image which may cause artifactssuch as overshoot and the like. Therefore, an image obtained byinversely transforming such image components contains components whichmay cause overshoot, and if that image is added, overshoot may occur.

To prevent this, in place of equation (20), it is effective to changehigh-frequency components by:h2n(x, y)=(1−f′(Org(x, y)))×fn(hn(x, y))  (22)

Note that the function fn( ) has a curve form shown in FIG. 7 or 8. Inimage components (high-frequency components), those generated at an edgehave values larger than normal components, and these curve forms setimage components corresponding to edge components to 0 or suppress them.As a result, in equation (22), when an image component is large, sincefn(hn(x, y)) becomes 0 or a suppressed value, h2n(x, y) also becomes 0or a suppressed value. On the other hand, when an image component has anormal value, h2n(x, y) becomes the same value as equation (20).

By adding the image obtained by computing the inverse DWTs of the imagecomponents given by equation (20) or (22) to the image that hasundergone the tone conversion, an image, the dynamic range of which hasbeen changed, but the high-frequency components of which have magnitudesnearly equal to those of the original image, can be obtained.

Furthermore, since the image components are changed in correspondencewith the magnitudes of image components as in equation (22), effectiveimage components (those equal to or lower than the predetermined value)of the high-frequency components become nearly equal to those of theimage before tone conversion. Since image components (those higher thanthe predetermined value) that cause overshoot of the high-frequencycomponents are not added, i.e., changed, or are added or changed whilebeing suppressed, overshoot or the like can be prevented or suppressed.By setting the slope of the function form fn( ) to be equal to or largerthan 1 (or larger than 1) within the range where the input value isequal to or smaller than the predetermined value, high-frequencycomponents can be emphasized while suppressing overshoot. Hence, thedynamic range and high-frequency components can be changed at the sametime while suppressing overshoot and the like.

In Embodiment 3, since the dynamic range change process is implementedby exploiting the multiple-frequency process, and high-frequencycomponents are adjusted in correspondence with tone conversion used tochange the dynamic range, a high-quality image, the dynamic range ofwhich has been changed, can be obtained. Furthermore, sincehigh-frequency components of the original image are used as those to beadded, high-frequency components of the processed image can accuratelycome closer to those of the original image. Also, since the DWT processneed be done only once, the computation time can be shortened. Moreover,the dynamic range and high-frequency components can be changed at thesame time while suppressing artifacts such as overshoot and the like. Inthis manner, a dynamic range change process such as dynamic rangecompression or the like and a sharpening process for each frequency bandby changing frequency components for each frequency band can besimultaneously executed to obtain a high-quality output image.

Embodiment 4

Embodiment 4 relates to an image process for obtaining the effects ofthe dynamic range change and frequency processes while preserving theedge structure. FIG. 11 is a block diagram showing the arrangement ofEmbodiment 4, and a description of the same processes as in Embodiment 1will be omitted.

Referring to FIG. 11, reference numeral 112 denotes an image processingcircuit; 2101, a frequency band decomposing circuit for decomposing anoriginal image into a plurality of frequency bands by wavelettransformation, Laplacian pyramid transformation, or the like to obtainfrequency coefficients; 2102, a coefficient conversion circuit forconverting the coefficients on the basis of the slope of a toneconversion curve used later to change the dynamic range; 2103, aninverse conversion circuit for inversely converting the coefficientsobtained by conversion by the coefficient conversion circuit 2102; and2104, a tone conversion circuit for changing the dynamic range of theimage, obtained by inverse conversion by the inverse conversion circuit2103.

FIG. 12 is a flow chart showing the flow of processes of the imageprocessing circuit 112 according to Embodiment 4 of the presentinvention. FIG. 13 shows an example of the coefficient conversion curveused in the coefficient conversion circuit 2102. In FIG. 13, theabscissa plots input coefficients, and the ordinate plots outputcoefficients.

Embodiment 4 will be described below along with the flow of processesshown in FIG. 12. The frequency band decomposing circuit 2101 executes atwo-dimensional discrete wavelet transformation process of an originalimage f(x, y), and outputs frequency coefficients (s2201). The frequencycoefficient decomposing method may be any method of wavelettransformation, Laplacian pyramid transformation, and the like. In thisembodiment, the image is decomposed into frequency coefficients HH1,HL1, LH1, . . . , LL for respective frequency bands usingtwo-dimensional discrete wavelet transformation.

The coefficient conversion circuit 2102 converts the frequencycoefficients in accordance with a tone conversion curve (e.g., aconversion curve shown in FIG. 5) Fo used in the tone conversion circuit2104 (s2202). In this case, only coefficients in a region 2301 equal toor lower than a predetermined absolute value (threshold value) areconverted, and those higher than the predetermined absolute value remainunchanged, as shown in FIG. 13. This predetermined absolute value isdetermined by experiments depending on the magnitudes of coefficientswith respect to the edge of an image. The edge structure can bepreserved when coefficients higher than the predetermined absolute valueremain unchanged, and artifacts such as overshoot and the like can besuppressed in a reconstructed image.

Assume that hn(x, y) are frequency coefficients of n levels, i.e.,coefficients of a region 2301 equal to or lower than a predeterminedabsolute value, and h2n(x, y) are coefficient values after hn(x, y) haveundergone coefficient conversion by:h2n(x, y)=f5(f(x, y))×(1/F′(x, y))×hn(x, y)  (23)

Note that the function f5( ) has a curve form which depends on the pixelvalues of the original image f(x, y) or its smoothed image, for example,a curve form that assumes a small value when the pixel value of theoriginal image f(x, y) or its smoothed image is equal to or lower than apredetermined pixel value, or assumes a large value when the pixel valueis higher than the predetermined pixel value. Note that a conversioncurve F2( ) in FIG. 13 expresses the above process, and the coefficientsof the region 2301 are not always linearly converted but are convertedbased on equation (23). Therefore, the conversion curve F2( ) can alsobe expressed by:F2(hn(x, y))=h2n(x, y) =f5(f(x, y))×(1/F′(x, y))×hn(x, y), when hn(x,y)≦ predetermined threshold value =hn(x, y), when hn(x, y)>predetermined threshold value  (23)′

The inverse conversion circuit 2103 inversely converts h2n(x, y)(inverse DWT) (S2203). A restored image f2(x, y) is then obtained. Thetone conversion circuit 2104 executes tone conversion of the restoredimage f2(x, y) by:f3(x, y)=F(f2(x, y))  (24)to obtain an image f3(x, y), the dynamic range of which has been changed(s2204).

As described above, according to Embodiment 4, since the frequencycoefficients are changed in advance on the basis of a curve form of toneconversion used to change the dynamic range, the magnitudes ofhigh-frequency components in an image, the dynamic range of which hasbeen changed, can be maintained nearly equal to those of high-frequencycomponents of the original image. Since coefficient values within thepredetermined absolute value range are not changed, the edge structurecan be preserved, and overshoot and the like can be suppressed even inan image which has undergone the frequency process and dynamic rangechange process.

In FIG. 13, the conversion function F2( ) has an undifferentiable anddiscontinuous point, but no artifacts such as false edges or the likeappear in the inversely converted image. This is because no structurewhich is visually recognized as a continuous boundary such as a line orthe like appears on the inversely converted image since coefficientshaving the predetermined absolute value (those corresponding to theundifferentiable and discontinuous point of the conversion curve) arerandomly distributed in the coefficient domain. That is, the waveletcoefficients are frequency coefficients, and a predetermined imagedomain is restored by the inverse wavelet transformation process incorrespondence with the magnitudes of frequency components. Note thatfrequency coefficients of the predetermined absolute value may often bearranged continuously in correspondence with the edge portion of animage in the coefficient domain. In such case, since a continuousstructure in the coefficient domain, which appears after coefficientconversion using a discontinuous function like the conversion functionF2( ), appears as a continuous structure along the edge portion even onthe restored image, it is not recognized as a false edge.

Since the original image is decomposed into multiple-frequencycoefficients, a noise suppression process, a sharpening process, or ahybrid process with other processes can be easily done. For example, inthe noise suppression process or the like, an analysis process or thelike based on coefficients upon decomposing the original image intomultiple-frequency coefficients is done, and predetermined frequencycoefficients are converted based on the analysis result or the like.

Another Embodiment

The scope of the present invention includes a case wherein the functionsof the embodiments are implemented by supplying a program code ofsoftware that implements the functions of the embodiments to a computer(or a CPU or MPU) in an apparatus or system connected to variousdevices, and making the computer in the system or apparatus operate thevarious devices in accordance with the stored program, so as to operatethe various devices for the purpose of implementing the functions of theembodiments.

In this case, the program code itself read out from the storage mediumimplements the functions of the embodiments, and the program codeitself, and means for supplying the program code to the computer (i.e.,a storage medium which stores the program code) constitutes the presentinvention.

As the storage medium for storing such program code, for example, afloppy disk, hard disk, optical disk, magneto-optical disk, CD-ROM,magnetic tape, nonvolatile memory card, ROM, and the like may be used.

The program code also constitutes the present invention not only whenthe functions of the embodiments are implemented by executing thesupplied program code by the computer but also when the functions of theembodiments are implemented by collaboration of the program code and anOS (operating system) or another application software running on thecomputer.

Furthermore, the program code constitutes the present invention when thefunctions of the embodiments are implemented by some or all of actualprocesses executed by a CPU or the like arranged in a function extensionboard or a function extension unit, which is inserted in or connected tothe computer, after the supplied program code is written in a memory ofthe extension board or unit.

As described above, according to the above embodiments, since toneconversion and conversion of frequency components based on it are madeusing the tone conversion process and multiple-frequency transformationprocess, a high-quality output image can be obtained.

When the dynamic range or predetermined pixel value range of an image ischanged by tone conversion, and high-frequency components are convertedbased on the slope of the tone conversion curve, a high-quality outputimage, the dynamic range or predetermined pixel value range of which hasbeen changed, can be obtained.

1-42. (canceled)
 43. An image processing apparatus comprising: a toneconversion unit arranged to execute tone conversion of an original imagebased on a tone conversion curve; a frequency transformation unitarranged to decompose the original image, or an image generated byexecuting the tone conversion of the original image, into coefficientsfor a plurality of high frequency bands and one low frequency band; acomponent conversion unit arranged to convert the coefficients of theplurality of high frequency bands by converting values of thosecoefficients based on a slope of the tone conversion curve; and aninverse frequency transformation unit arranged to generate an imagebased on the converted coefficients.
 44. The apparatus according toclaim 45, wherein the threshold values are determined based on thecoefficients forming an edge of the original image.
 45. The apparatusaccording to claim 43, wherein the component conversion unit setsthreshold values each corresponding to respective one of the pluralityof frequency bands and the low frequency band, and converts thecoefficient whose value is less than the corresponding threshold value.46. The apparatus according to claim 43, wherein the componentconversion unit converts values of the coefficients corresponding to alowest frequency band to zero.
 47. The apparatus according to claim 43,wherein the component conversion unit does not convert a coefficient ofa lowest frequency band.
 48. The apparatus according to claim 43,wherein the frequency transformation unit and the inverse frequencytransformation unit respectively perform decomposition and imagegeneration based on any one of: discrete wavelet transformation,Laplacian pyramid transformation, and moving average techniques.
 49. Theapparatus according to claim 43, further comprising: an X-ray generatorarranged to emit X-rays to an object; and a two-dimensional X-ray sensorarranged to convert X-rays transmitted through the object, wherein theoriginal image is captured by the two-dimensional X-ray sensor.
 50. Animage processing method comprising: a tone conversion unit arranged toexecute tone conversion of an original image based on a tone conversioncurve; a frequency transformation step of decomposing the originalimage, or an image generated by executing the tone conversion of theoriginal image, into coefficients for a plurality of high frequencybands and one low frequency band; a component conversion step ofconverting the coefficients of the plurality of high frequency bands byconverting values of those coefficients based on a slope of the toneconversion curve; and an inverse frequency transformation step ofgenerating an image based on the converted coefficients.
 51. Acomputer-readable medium encoded with a computer program for a method ofprocessing an image, the method comprising: a tone conversion unitarranged to execute tone conversion of an original image based on a toneconversion curve; a frequency transformation step of decomposing theoriginal image, or an image generated by executing the tone conversionof the original image, into coefficients for a plurality of highfrequency bands and one low frequency band; a component conversion stepof converting the coefficients of the plurality of high frequency bandsby converting values of those coefficients based on a slope of the toneconversion curve; and an inverse frequency transformation step ofgenerating an image based on the converted coefficients.